Smart Enough Systems

I’m sure that James Taylor has almost given up on me ever writing a book review of Smart Enough Systems: I wrote a brief advance review back in April that’s printed in the book, but nothing since it was released. This week, I’ve been immersed in business rules and decisioning, and had a chance to finally meet James face-to-face after a couple of years of emailing back and forth. Also, James’ situation has changed since the book was released: he’s left Fair Isaac and is now an independent, working (I think) with his co-author, Neil Raden. Neil, who I met very briefly this week, is an independent consultant and analyst who’s been focussed on business intelligence for quite a while; James refers to his work as “BI 2.0” (a term that I think that I invented here in early 2006). The two of them met through James’ blog and started the conversation about how someone needed to write a book about this crossover area between business rules and business intelligence.

Just to get started, here’s my pre-release review:

Taylor and Raden’s central manifesto highlights that it’s critical to embody more intelligence in today’s business decision-making and have consistent, automated decisioning built into business processes in order to remain agile and competitive in today’s fast-moving market. They take you through the core concepts of enterprise decision management (EDM), dive into the underlying technologies, then address how to integrate EDM into your business processes to create your own Smart (Enough) Systems.

By focusing on operational decisions that contribute to corporate strategy, Smart (Enough) Systems provide the ability not only to create agile business processes, but to have these processes be self-learning based on historical results. Instead of simply capturing operational process statistics in a data warehouse for later analysis, Smart (Enough) Systems use that knowledge to inform the business rules and allow them to adapt their guidance of the decision-making process. By extracting the decisions from legacy applications, static enterprise applications and manual procedures, and managing them within a shared enterprise decision management system, operational decisions can be applied consistently — and modified easily for processes in flight — across the enterprise.

What I like about the book is that it provides an overview that will get business people interested in the topic, as well as providing a practical guide to getting started. There’s a lot of books focussed on analytics and business rules already, but most of them assume that you already know what you’re going to do with these technologies; in many cases, it’s hard to discover the right decisions on which to focus, since some things are more important than you may have originally perceived when starting a project.

As I heard this week, there’s still a strong tendency to sell rules technology to IT as a way to implement systems fast and cheaper, instead of selling decisioning to the business as a way to solve business problems. For the most part, decisions in business processes are unconsciously relegated either to a developer coding them into an application, or to a front-line worker executing them on an ad hoc basis. Decisions, and the rules that underlie them, need to be made explicit: therein lies the path to both compliance and agility. I joked yesterday about Jan Venthienen’s presentation that he’d like to reduce all processes to a single activity and have all business logic in a rule set, but there’s definitely value in what he’s saying: we need to seek out the decisions in processes, capture the ever-changing business rules that are embedded within them, and move these out of the processes and into rules/decisioning systems. The reality is that process maps don’t change all that often if the decisions and business rules are stripped out of the processes: most business agility is based on rule changes, not process changes, especially for high-volume core transactional processes. However, since we often code rules directly into the business processes — making these processes some combination of processes and decision trees — we perceive the need to be that of changing processes rather than changing rules. And so (and I’ll be totally blackballed in the BPM community for this particular blasphemy), the entire BPM industry has focussed on building tools that allow for easy modification of process maps by the business, when maybe they really should have been focussed on pushing their customers towards the integration of business rules for decisioning in order to greatly reduce the need to modify process maps.

Climbing off my soapbox for a moment and returning to James and Neil’s book, they focus on a key benefit of this sort of smart decisioning in operational processes, which is the ability to replace the “irreplaceables”, such as insurance underwriters, before all the boomers take their knowledge and retire to Palm Beach. This greatly controls risk: not just the risk of the workers leaving, but the risk of bad or inconsistent decision-making. By allowing decisions to become more personalized based on the customer and scenario, this can also provide the ability to be more customer-centric, as well as agility in the face of changing regulations and market conditions.

They see a number of roadblocks to this sort of smart decisioning at the operational level:

Everyone is focussed on strategic issues and not taking their operations seriously; however, the aggregate effect of a small but poor decision on millions of operational transactions is, in fact, strategic. In other words, execution matters.

Business and IT have an antagonistic relationship. This is often blamed on IT being arrogant and not allowing the business to participate in technology initiatives, but there’s also some amount of the business not wanting to take responsibility since that means that they can’t blame IT if something goes wrong.

The ideas that James and Neil put forward in their book are a great place for business and IT to start collaborating on how to make smart enough systems.